Multivariate many-to-one procedures with applications to preclinical trials

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Kropf, S.; Hothorn, L.A.; Läuter, J.: Multivariate many-to-one procedures with applications to preclinical trials. In: Therapeutic Innovation & Regulatory Science 31 (1997), Nr. 2, S. 433-447. DOI: https://doi.org/10.1177/009286159703100214

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Sum total of downloads: 103




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Abstract: 
Comparisons of several treatments with a control represent a standard situation in preclinical trials. Usually, they are considered with a single variable, resulting in multiple test procedures such as the Dunnett test (1). Here, the multivariate many-to-one problem is considered, where several variables are observed on each individual of the control and treatment groups. Classical MANOVA tests and their derivatives for the many-to-one problem require large sample sizes in order to be powerful if the dimension is high. In this paper, a new class of stabilized multivariate tests proposed by Läuter (2) and Läuter, Glimm, and Kropf (3) is extended to this special design. The new tests are based on linear scores which are derived in a certain way from the original variables. They utilize factorial relations among the variables. It is shown here that the procedures keep the multiple level. In simulation experiments several versions of multivariate tests are compared with each other. Standard approaches are included as well as different score versions and a comparison of Dunnett-like procedures with Bonferroni-type procedures. Generally, an improved power of the new tests compared to standard procedures is demonstrated. © 1997, Drug Information Association. All rights reserved.
License of this version: Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden. Dieser Beitrag ist aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.
Document Type: Article
Publishing status: publishedVersion
Issue Date: 1997
Appears in Collections:Naturwissenschaftliche Fakultät

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pos. country downloads
total perc.
1 image of flag of Germany Germany 48 46.60%
2 image of flag of France France 15 14.56%
3 image of flag of Philippines Philippines 7 6.80%
4 image of flag of United States United States 6 5.83%
5 image of flag of China China 3 2.91%
6 image of flag of Canada Canada 3 2.91%
7 image of flag of Ukraine Ukraine 2 1.94%
8 image of flag of Taiwan Taiwan 2 1.94%
9 image of flag of Japan Japan 2 1.94%
10 image of flag of Switzerland Switzerland 2 1.94%
    other countries 13 12.62%

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